Explore & Summarize Data by Yasser Arafath
This data set cosists of the fatal accidents which occured in US from the year 1998 to 2011. The variables present are Age, State, No of Airbags in the car, if Airbags were deployed, the injury level for driver, etc. There are many missin values, these are handled by creating subsets of the dataset.
Summary of the dataset:
## year caseid state age
## Min. :1998 1.031956019: 36 Min. : 1.00 Min. : 0.00
## 1st Qu.:2000 1.038900463: 36 1st Qu.:12.00 1st Qu.: 19.00
## Median :2003 1.013900463: 35 Median :27.00 Median : 26.00
## Mean :2004 1.011122685: 34 Mean :27.23 Mean : 34.85
## 3rd Qu.:2006 0.961122685: 33 3rd Qu.:42.00 3rd Qu.: 48.00
## Max. :2010 0.993761574: 33 Max. :56.00 Max. :100.00
## (Other) :150951 NA's :2762
## sex D_injury D_airbagAvail D_airbagDeploy
## Min. :1.00 Min. :0.00 no :45087 no :78480
## 1st Qu.:1.00 1st Qu.:1.00 yes :98839 yes :51582
## Median :2.00 Median :3.00 NA's: 7232 NA's:21096
## Mean :1.51 Mean :2.47
## 3rd Qu.:2.00 3rd Qu.:4.00
## Max. :2.00 Max. :5.00
## NA's :879A histogram is created to see the number of accidents caused by the age groups
This histogram shows that the people between age 15-25 cause the most number of accidents
A histogram is created to see the number of accidents caused every year from 1998-2011
This histogram shows that the number of accidents caused each year is decreasing.
A histogram to see which sex caused the most number of accidents
It is seen that females are marginally greater in count compared to males
A histogram to see if the cars were equipped with airbags
It is seen that majority of the cars were equipped with airbags & still faced a fatal acciddent
A histogram to see the deployment of airbag during the accident
The airbags wernt deployed in majority of the accidents, from which we can infer that airbags play an important role in safety
A histogram to see the deployment of airbag in the airbag available cars
This graph is to show the ratio of how the airbags were deployed in the airbag available cars
A histogram to see the number of accident in every State
The highest number of accidents were caused in State “6”
Univariate Analysis
What is the structure of your dataset?
This dataset is a list of all the fatal accidents which occured in the US from the year 1998 to 2011.
What is/are the main feature(s) of interest in your dataset?
The main feature of this dataset is that it shows the number of accidents happened in each year from 1998 to 2011 by sex.
What other features in the dataset do you think will help support your
investigation into your feature(s) of interest?
The cause of the accident & the time of occurance will help in the investigation further.
Did you create any new variables from existing variables in the dataset?
Yes, a subset of the dataset without the ‘NA’ values for ‘sex’ & ‘Age’ was created. And a subset of data having only cars with airbag was created.
Of the features you investigated, were there any unusual distributions?
Did you perform any operations on the data to tidy, adjust, or change the form
of the data? If so, why did you do this?
There wernt any unusuall distributions, the dataset was clean already.
Bivariate Plots Section
These are graphs obtained by comparing 2 variables
We first group the values by age and sex
Accident data are first seperated by sex
A bargraph of accidents by age is created only for Men
A bargraph of accidents by age is created only for Women
The graphs are put side by side for a better comparision
A histogram is created comparing the age with the mean of the injury values
Age vs Injury
A scatterplot is created comparing the sex with the mean of the injury values
Age vs Injury by Sex
A boxplot is created comparing the age with the injury values
A boxplot to compare Age vs Injury by Sex
From the previous histogram, it was seen that the states ‘6’, ‘48’ & ‘12’ had the highest number of accidents.
Here We create seperate bar graphs state wise to show the number of accidents in the top 3 states by age group
A grid is created to show the top states which had the highest number of accidents
A boxplot is created comparing the age with the Airbag Availability
A boxplot to compare Age vs Airbag Availability
Bivariate Analysis
From the 1st histogram it is observed that mean of injury is uniform across the various age groups, except for ages above 90 & From the scatterplot, men from various age groups suffered higher injury compared to women of that age group
Talk about some of the relationships you observed in this part of the
investigation. How did the feature(s) of interest vary with other features in
the dataset?
In this part, the injury level of the victim was compared to the age. It was found that it did not vary much across the age groups.
Did you observe any interesting relationships between the other features
(not the main feature(s) of interest)?
Injury level between the sex was observed, it was found that male were prone to higher injury than the female victim in the 20-50 age group.
What was the strongest relationship you found?
People from age group 75-85 suffered the most injury
Multivariate Plots Section
A Graph is generated to compare Age vs Sex vs Year
From this graph, we can see that the blue color is on the top portion of the graph and brown is spread at the bottom of the graph. i.e Females with age higher than 70 face more accidents compared to men throughout the years.
A Boxplot to represent how every year each sex face the accident
This is another detailed representation of how every year each sex face the accident
A Histogram to see which age group met with the highest number of accident in top 3 states by age group
Number of accidents by Age group in Top 3 states
A Boxplot to see the level of Injury by age in ascending order
A boxplot to indicate the injury level in order
A level plot to compare Injury lever and age by year
Multivariate Analysis
Talk about some of the relationships you observed in this part of the
investigation. Were there features that strengthened each other in terms of
looking at your feature(s) of interest?
From this Multivariate Analysis, we observed that the majority of victims in age group 70-90 were females and in the age group 20-50 the majority is males
Were there any interesting or surprising interactions between features?
Three were nothing surprising or interesting
Final Plots and Summary
Plot One
This is one of the importang histograms as this shows which age group faced the most faality. From this histogram, we can infer that people from age 15-25 faced the most number of accidents.
Plot Two
This Graph shows how much injury different sex faced in the crash. Males from age 20-50 faced severe injury compared to females. and females from age 70-90 faced higher injury rate than males of that group
Plot Three